Previous studies have highlighted the importance of promoting health literacy and minimizing misinformation to encourage higher adherence to key public health measures during the COVID-19 pandemic. This study explores how one’s self-reported understanding of information and types of sources used to get information regarding COVID-19 can hinder adherence to public health measures implemented by the Canadian government. Data was collected following a longitudinal design of 11 time points for April 2020 to April 2021. The sub-sample used for this study included 2659 Canadians who completed the survey for at least four time points. Using Latent Class Growth Analysis, we modelled typical trajectories of adherence to three key public health measures: staying home, social distancing and mask wearing. Overall, a lower level of understanding was associated with lower adherence trajectories to public health measures, and vice-versa. Adjusted odds ratio (AOR) showed that the higher the level of understanding, the higher were the chances of following a high adherence trajectory. The type of used sources also showed a significant statistical association with adherence trajectories for social distancing and staying home (AOR: between 1.1 and 3.4). These results are discussed considering future policy implications.

IntroductionWe investigated whether initial risk classes and heterogeneous trajectories of self-compassion over the course of the pandemic may impact well-being outcomes 1 year into the pandemic.MethodsA large, representative sample of Canadians (N = 3,613; 50.6% women) was sampled longitudinally over 11 waves (April 2020–April 2021), using a rolling cross-sectional survey design. Analyses were conducted in three steps: (1) latent class analysis to identify heterogeneity in risk factors (sociodemographic, cognitive-personality, health-related) early in the pandemic, (2) latent class growth analysis (LCGA) to identify longitudinal self-compassion trajectories, and (3) GLM to examine effects of risk factor classes and self-compassion trajectories, as well as their interaction, on later well-being (mental health, perceived control, life satisfaction).Results and DiscussionFour risk factor classes emerged, with 50.9% of participants experiencing low risk, 14.3% experiencing multiple risks, 20.8% experiencing Cognitive-Personality and Health risks, and 14.0% experiencing sociodemographic and Cognitive-Personality risks. Four self-compassion trajectories also emerged, with 47.7% of participants experiencing moderate-high self-compassion that decreased then stabilized, 32.0% experiencing moderate self-compassion that decreased then stabilized, 17.3% experiencing high and stable self-compassion across time, and 3.0% experiencing low and decreasing self-compassion. Comparisons of well-being outcomes 1 year post-pandemic indicated that higher levels of self-compassion over time may protect against the impact of initial risk on well-being outcomes. Further work is still needed on heterogeneity in experiences of risk and protective factors during stressful life events.

ObjectivesPrevious studies found a general increase in prejudice against Chinese people during the first months of the pandemic. The present study aims to consider inter-individual heterogeneity in stability and change regarding prejudice involving Chinese people during the pandemic. The first objective is to identify and describe different trajectories of prejudice over a seven-month period during the pandemic. The second and third objectives are to test the association between trajectory group membership and antecedent variables such as: socio-demographic factors (i.e., age, gender, political affiliation) and two psychological mechanisms, namely economic threat and global citizenship identification.MethodsA representative Canadian sample (N = 3,617) according to age, gender and province of residence, was recruited for a 10-wave survey starting from April 2020 to December 2020. First, a group-based modeling approach was used to identify trajectories of prejudice. Second, a multinomial logistic regression model was used to test associations between membership in trajectories and antecedents.ResultsFour trajectories were identified. The first three trajectories have a low (71.4% of the sample), high (18.5%) or very high (5.3%) level of prejudice against Chinese people which is relatively stable over time. The fourth trajectory (4.9%) reports low levels of prejudice in favor of Chinese people which become more positive throughout 2020. Regarding socio-demographic factors: gender is not associated with trajectory group membership, younger people are more likely to follow the trajectory in favor of Chinese people and conservatives are more likely to follow the highest trajectories against Chinese people. Regarding some psychological mechanisms: personal but not collective economic threat is associated with the trajectory in favor of Chinese people. Finally, the highest levels of prejudice are found when the strategy of identification is more local rather than global.ConclusionThe present study shows that Canadians differ in terms of both their level and change in prejudice against Chinese people throughout the pandemic with some socio-demographic groups being more likely than others to be associated with prejudice. The results also suggest that a promising way to tackle the major social issue of prejudice is to highlight a vision of the world where individuals are all “global citizens” facing the same challenge.

While analyzing data, researchers are often faced with missing values. This is especially common in longitudinal studies in which participants might skip assessments. Unwanted missing data can introduce bias in the results and should thus be handled appropriately. However, researchers can sometimes want to include missing values in their data collection design to reduce its length and cost, a method called "planned missingness." This paper review the recommended practices for handling both planned and unplanned missing data, with a focus on longitudinal studies. The current guidelines suggest to either use Full Information Maximum Likelihood or Multiple Imputation. Those techniques are illustrated with R code in the context of a longitudinal study with a representative Canadian sample on the psychological impacts of the COVID-19 pandemic.

Previous studies have highlighted the importance of promoting health literacy and minimizing misinformation to encourage higher adherence to key sanitary measures during the COVID-19 pandemic. This study explores how one’s understanding of information and sources’ reliability can hinder adherence to sanitary measures implemented by the Canadian government. Data was collected from a representative sample of 3,617 Canadians, following a longitudinal design of 11 measurement times from April 2020 to April 2021. Overall, a low level of understanding was associated with membership in lower adherence trajectories to sanitary measures. Adjusted odds ratio (AOR) showed it was between 3 and 34 times more likely for participants with low understanding to be in the lowest adherence trajectory. Information sources’ reliability also showed a significant effect on adherence trajectories for social distancing and staying home (AOR: between 1.5 and 2.5). These results are discussed considering future policy implications.